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Genome-wide association studies (GWAS) of complex behavioural phenotypes such as cigarette smoking typically employ self-report phenotypes. However, precise biomarker phenotypes may afford greater statistical power and identify novel variants. Here we report the results of a GWAS meta-analysis of levels of cotinine, the primary metabolite of nicotine, in 4,548 daily smokers of European ancestry. We identified a locus close to UGT2B10 at 4q13.2 (minimum p = 5.89 × 10(-10) for rs114612145), which was consequently replicated. This variant is in high linkage disequilibrium with a known functional variant in the UGT2B10 gene which is associated with reduced nicotine and cotinine glucuronidation activity, but intriguingly is not associated with nicotine intake. Additionally, we observed association between multiple variants within the 15q25.1 region and cotinine levels, all located within the CHRNA5-A3-B4 gene cluster or adjacent genes, consistent with previous much larger GWAS using self-report measures of smoking quantity. These results clearly illustrate the increase in power afforded by using precise biomarker measures in GWAS. Perhaps more importantly however, they also highlight that biomarkers do not always mark the phenotype of interest. The use of metabolite data as a proxy for environmental exposures should be carefully considered in the context of individual differences in metabolic pathways.

Introduction: Our aim was to understand the strength of association between parental smoking and child environmental tobacco smoke (ETS) exposure in order to inform the development of future tobacco control policies. ETS was measured using child cotinine levels below the active smoking threshold., Methods: Participants were drawn from the Avon Longitudinal Study of Parents and Children and included 3,128 participants at age 7 years and 1,868 participants at age 15 years. The primary outcome was cotinine levels of nonsmoking children, to investigate the relationship between maternal smoking and child cotinine levels. The secondary outcome was cotinine levels of all individuals to investigate the relationship between child smoking and child cotinine levels. Maternal and child smoking behavior was assessed by self-report questionnaire. We adjusted for several sociodemographic variables., Results: We found an association between maternal smoking and child cotinine at age 7 years (mean cotinine = 1.16ng/ml serum, ratio of geometric means = 3.94, 95% CI = 2.86-5.42) and at age 15 years (mean cotinine = 0.94ng/ml serum, ratio of geometric means = 5.26, 95% CI = 3.06-9.03), after adjustment for potential confounders., Conclusions: The magnitude of this association for children whose mothers were heavy smokers was comparable with the quantity of half the levels of cotinine observed among children who were irregular (i.e., nonweekly) active smokers, and it was greater than five times higher than that seen in nonsmoking children whose mothers didn't smoke. This provides further evidence for the importance of public health interventions to reduce smoking exposure in the home.

Aims To investigate the relationship between cannabis and tobacco use by age 15 and subsequent educational outcomes. Design Birth cohort study. Setting England. Participants The sample was drawn from the Avon Longitudinal Study of Parents and Children; a core sample of 1155 individuals had complete information on all the variables. Measurements The main exposures were cannabis and tobacco use at age 15 assessed in clinic by computer-assisted questionnaire and serum cotinine. The main outcomes were performance in standardized assessments at 16 [Key Stage 4, General Certificate of Secondary Education (GCSE)] in English and mathematics (mean scores), completion of five or more assessments at grade C level or higher and leaving school having achieved no qualifications. Analyses were sequentially adjusted for multiple covariates using a hierarchical approach. Covariates considered were: maternal substance use (ever tobacco or cannabis use, alcohol use above recommended limits); life course socio-economic position (family occupational class, maternal education, family income); child sex; month and year of birth; child educational attainment prior to age 11 (Key Stage 2); child substance use (tobacco, alcohol and cannabis) prior to age 15 and child conduct disorder. Findings In fully adjusted models both cannabis and tobacco use at age 15 were associated with subsequent adverse educational outcomes. In general, the dose-response effect seen was consistent across all educational outcomes assessed. Weekly cannabis use was associated negatively with English GCSE results [grade point difference (GPD), -5.93, 95% confidence interval (CI) = -8.34, -3.53] and with mathematics GCSE results (GPD, -6.91, 95% CI = -9.92, -3.89). Daily tobacco smoking was associated negatively with English GCSE (GPD, -11.90, 95% CI = -13.47, -10.33) and with mathematics GCSE (GPD, -16.72, 95% CI = -18.57, -14.86). The greatest attenuation of these effects was seen on adjustment for other substance use and conduct disorder. Following adjustment, tobacco appeared to have a consistently stronger effect than cannabis. Conclusions Both cannabis and tobacco use in adolescence are associated strongly with subsequent adverse educational outcomes. Given the non-specific patterns of association seen and the attenuation of estimates on adjustment, it is possible that these effects arise through non-causal mechanisms, although a causal explanation cannot be discounted. © 2015 Society for the Study of Addiction [ABSTRACT FROM AUTHOR]